Network traffic volumes generally continue to increase at a rapid pace. On some networks, this increase has been particularly due to the high adoption of services that have high demand for data throughput, for example, video services such as Netflix™ and the like. Because of this increase in traffic volumes, mobile and broadband Internet Service Providers (ISPs) are striving to keep their network capable of delivering the requested content at all times.
The problem of network volumes and capacity typically becomes most important at certain times throughout the day when the network is being used the most, typically called the peak times or period(s). At these times, the high demand for Internet traffic may be more than what the network is capable of (i.e. exceed network capacity), which consequently can result in poor quality of experience for end users/subscribers and, as such, may result into subscriber churn, where disgruntled subscribers may move to a different ISP. For this reason, ISPs typically put a high emphasis on predicting their network growth and planning their capacity and optimization to ensure that their networks have capacity to meet demand even during peak periods.
Capacity planning and optimization decisions are typically driven by budget concerns and general company strategy; these decisions are typically made at senior management levels of an ISP. In some cases, these decisions are made based on data from thousands of network resources serving millions of subscribers. Conventional capacity planning and optimization systems and methods attempt to use overall data volumes and peak period information to predict future network resources.
In network capacity planning, there is an ongoing need to identify the problems with the current approaches and provide improved systems and methods.